Song Li

61 total papers · 1.7k total citations
41 papers, 1.4k citations indexed

About

Song Li is a scholar working on Molecular Biology, Epidemiology and Rheumatology. According to data from OpenAlex, Song Li has authored 41 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 6 papers in Epidemiology and 6 papers in Rheumatology. Recurrent topics in Song Li's work include Folate and B Vitamins Research (5 papers), Pregnancy and preeclampsia studies (3 papers) and Retinal Diseases and Treatments (2 papers). Song Li is often cited by papers focused on Folate and B Vitamins Research (5 papers), Pregnancy and preeclampsia studies (3 papers) and Retinal Diseases and Treatments (2 papers). Song Li collaborates with scholars based in China and United States. Song Li's co-authors include Shulin Li, Jun Yan, Shi-xin Hong, R. J. Berry, Jon D. Erickson, Joseph Mulinare, Cynthia A. Moore, Zhu Li, Jun-chi Zheng and Zhu Li and has published in prestigious journals such as The Lancet, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Song Li

39 papers receiving 1.4k citations

Hit Papers

The Role of the Liver in ... 2014 2026 2018 2022 2014 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Song Li 458 287 218 202 177 41 1.4k
Fan Yang 539 1.2× 504 1.8× 72 0.3× 204 1.0× 149 0.8× 42 1.7k
Farès Namour 606 1.3× 718 2.5× 243 1.1× 116 0.6× 199 1.1× 50 1.7k
Katalin Fekete 322 0.7× 208 0.7× 215 1.0× 113 0.6× 118 0.7× 33 1.5k
Yeon‐Joo Lee 357 0.8× 477 1.7× 180 0.8× 151 0.7× 213 1.2× 29 1.2k
Francine Einstein 451 1.0× 163 0.6× 246 1.1× 282 1.4× 118 0.7× 30 1.2k
Mercedes García-Bermúdez 606 1.3× 249 0.9× 298 1.4× 137 0.7× 66 0.4× 53 1.5k
Silvio Zaina 1.1k 2.5× 127 0.4× 257 1.2× 134 0.7× 184 1.0× 63 1.7k
Gloria Bonaccorsi 411 0.9× 69 0.2× 181 0.8× 162 0.8× 138 0.8× 74 1.7k
Hansjosef Böhles 546 1.2× 110 0.4× 384 1.8× 144 0.7× 85 0.5× 50 1.7k
Maria Cekanova 560 1.2× 96 0.3× 68 0.3× 133 0.7× 139 0.8× 51 1.7k

Countries citing papers authored by Song Li

Since Specialization
Citations

This map shows the geographic impact of Song Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Song Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Li more than expected).

Fields of papers citing papers by Song Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Song Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Song Li. The network helps show where Song Li may publish in the future.

Co-authorship network of co-authors of Song Li

This figure shows the co-authorship network connecting the top 25 collaborators of Song Li. A scholar is included among the top collaborators of Song Li based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Song Li. Song Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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